Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using categories that you feel may influence fuel efficiency. Answer the following questions.
Identify the two categories you chose and why you thought there might be a relationship between the two BEFORE creating the scatterplot?
Answer: We chose horsepower and weight as the factors that would have the greatest impact on fuel economy. It seems apparent that the the more powerful an engine the more fuel it will require. Also a heavier vehicle will require more energy to move...thus will require more fuel
Create the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer: We chose to use fuel economy as the y-axis data since it is the quantity that represents the dependent variable. Fuel economy represents the effect. Weight and horsepower were the independent variables so they were placed on the xaxis.
Do you believe there is a relationship between the two categories? Why or why not?
Answer: Horsepower: Yes, as the power increases there a noticeable decrease in fuel economy.
Weight: Yes, as the weight increases there a noticeable decrease in fuel economy.
If there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Answer: Both have a negative or inverse realtionship. This means as weight or horsepower increases the fuel economy will decrease.
Regression Questions
Create the linear regession equation in Excel. Include both the equation and the r2 value on the graph. Answer the following questions.
What is your regression equation? Explain what the equation means in relation to the categories.
Answer: y= -0.0676x + 35.448 (horsepower) This means that for an increase of 1 horsepower there is a decrease of 0.0676 mpg. y=-0.0077x + 49.325
What is your r2 value? Is this a strong correlation? Why or Why not?
Answer: This means there is definitely an inverse relationship between horsepower and fuel economy but the relationship is not as strong as the relationship between weight and fuel economy.
Based on all the information you have, can you make any conclusions about your two categories? If so, what conclusions can you make? If not, why not?
Answer: Weight has a stronger correlation than horsepower on fuel economy of the vehicle.
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
How would you determine which equation had the best relationship?
Answer:
Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Answer:
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.
Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using categories that you feel may influence fuel efficiency. Answer the following questions.
Answer: We chose horsepower and weight as the factors that would have the greatest impact on fuel economy. It seems apparent that the the more powerful an engine the more fuel it will require. Also a heavier vehicle will require more energy to move...thus will require more fuelIdentify the two categories you chose and why you thought there might be a relationship between the two BEFORE creating the scatterplot?
Answer: We chose to use fuel economy as the y-axis data since it is the quantity that represents the dependent variable. Fuel economy represents the effect. Weight and horsepower were the independent variables so they were placed on the xaxis.Create the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer: Horsepower: Yes, as the power increases there a noticeable decrease in fuel economy.Do you believe there is a relationship between the two categories? Why or why not?
Weight: Yes, as the weight increases there a noticeable decrease in fuel economy.
Answer: Both have a negative or inverse realtionship. This means as weight or horsepower increases the fuel economy will decrease.If there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Regression Questions
Create the linear regession equation in Excel. Include both the equation and the r2 value on the graph. Answer the following questions.
Answer: y= -0.0676x + 35.448 (horsepower) This means that for an increase of 1 horsepower there is a decrease of 0.0676 mpg. y=-0.0077x + 49.325What is your regression equation? Explain what the equation means in relation to the categories.
Answer: This means there is definitely an inverse relationship between horsepower and fuel economy but the relationship is not as strong as the relationship between weight and fuel economy.What is your r2 value? Is this a strong correlation? Why or Why not?
Answer: Weight has a stronger correlation than horsepower on fuel economy of the vehicle.Based on all the information you have, can you make any conclusions about your two categories? If so, what conclusions can you make? If not, why not?
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
Answer:How would you determine which equation had the best relationship?
Answer:Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.